Data sets with hundreds of variables or more arise today in many contexts. Examples include: gene expression data for uncovering the link between the genome and the various proteins for which it codes; demographic and consumer profiling data for capturing underlying sociological and economic trends; sales and marketing data for huge numbers of products in vast and ever-changing marketplaces; and environmental measurements for understanding phenomena such as pollution, meteorological changes, and resource impact issues.
Data visualization is a powerful tool for exploring large data sets, both by itself and coupled with data mining algorithms. Graphical views provide user-friendly ways to visualize and interpret data. However, the task of effectively visualizing large databases imposes significant demands on the human-computer interface to the visualization system.
In addition, as computing and networking speeds increase, data visualization that was traditionally performed on desktop computers can also be performed on portable electronic devices, such as smart phones, tablets, and laptop computers. These portable devices typically use touch-sensitive surfaces (e.g., touch screens and/or trackpads) as input devices. These portable devices typically have smaller displays than desktop computers. Thus, additional challenges arise in using touch-sensitive surfaces to manipulate graphical views of data in a user-friendly manner on portable devices.
Consequently, there is a need for faster, more efficient methods and interfaces for manipulating graphical views of data. Such methods and interfaces may complement or replace conventional methods for visualizing data. Such methods and interfaces reduce the cognitive burden on a user and produce a more efficient human-machine interface. For battery-operated devices, such methods and interfaces conserve power and increase the time between battery charges.